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Establish + Real-time display of Blockchain trust #2905
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Required background reading:
Different sub-projects all form the key components of the total project.
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And a permanent record for GitHub. The groups have been assigned based on their preferences:
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Implementation of our scalable blockchain (TrustChain): https://github.com/Tribler/tribler/tree/devel/Tribler/community/multichain |
Progress overviewA total of 20 student in 4 teams. All teams have produced a prototype.
other Delft team with operational Android blockchain, not trustchain |
ChainableTech |
Draft for the NervousFish app (i.e. Team: Android app with easy to use pairing) can be found |
Final reports and information. |
All of our deliverables in a single zip. |
All deliverables (including the final report) for the Nervoush Fish app can be downloaded here |
deliverables for Bulls, Bears & Wolves |
Releases of self-sovereign identity Android Apps:
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All work now moved to #10, closing this issue. |
this is the master ticket of the TI2806 Blockchain Context Project
All major updates will be displayed here.
This is a cutting edge research project within a highly competitive emerging research area. This assignment is suitable for scientific publication, ambitious students, and honor track participants.
Within this project you will build a solution to establish + visualize trust. The basic technique of using reputations to craft trust has been pioneered 22 years ago by eBay. Showing rating of both sellers and buyers on marketplaces provide basic trustworthiness hints. Online market Silk Road created honesty amongst online drug dealers using simplistic trust building mechanism, resulting in a 2.2% ratio of unsatisfactiory deals.
We build trust based upon well-known techniques of tamper-proof datastructures, recently popular under the name blockchain. For basic information about Blockchain technology, see this online book: https://d28rh4a8wq0iu5.cloudfront.net/bitcointech/readings/princeton_bitcoin_book.pdf or the video lectures: http://bitcoinbook.cs.princeton.edu/
A blockchain database is provided, used to retrieve various transaction records, you must use these transactions to calculate trust scores. Trust scores need to be updated in real-time. As a starting point you will get a real-world blockchain transactions dataset in SQLight. An existing (expensive) algorithm in Python is provided. You will need to explore the literature on algorithms such as PageRank and EigenTrust to understand various performance trade-offs. You will need to understand how to visualize trust and other constraints. Will your work scale to blockchain databases with 10k or even 100k transactions? Your final product will be a tested and documented piece of software, superior to existing prototype:
https://github.com/Tribler/ /issues/2803
Current operational implementation to show trust within a Bittorrent client with Tor-like relay protocol:

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